Date: Thursday 22nd October 2026 Time: 15:00 - 16:00 GMT Location: Online via Zoom
Who is this event intended for?Statisticians with an interest in vaccine development
What is the benefit of attending? To learn about the recent application of statistical immune correlate analysis in vaccine development. Specifically, an application of such analyses to evaluate hemagglutination inhibition titers for an influenza vaccine
Overview
Hemagglutination inhibition antibody (HAI) titers are widely utilized as correlates of protection (CoP) and surrogate endpoints for predicting influenza vaccine efficacy (VE). In the phase 3 FLUENT trial (NCT06602024), which enrolled over 40,000 participants ≥50 years, the mRNA-based seasonal influenza vaccine, mRNA-1010, demonstrated superior VE and elicited stronger antibody responses than a licensed standard-dose inactivated influenza vaccine.
Here, in the immune correlate analysis of the FLUENT trial, we evaluated hemagglutination inhibition (HAI) titers against influenza A/H1N1, A/H3N2, and B/Victoria strains as correlates of risk (CoR) and CoP for strain-specific influenza-like illness (ILI) following vaccination. Across multiple statistical and causal inference frameworks, higher Day 29 influenza A strain-specific HAI titers were consistently associated with lower ILI and higher relative VE. The estimated hazard ratios per one standard deviation increase in HAI titers were 0.48 (95% CI: 0.43–0.54; P<0.001) for A/H1N1 and 0.66 (0.58–0.74; P<0.001) for A/H3N2.
Although B/Victoria results in FLUENT were inconclusive, likely reflecting limited cases and regional variability, pooled analyses across phase 3 trials showed consistent inverse associations for both vaccines. These findings support post-vaccination HAI titers as a statistical CoP and surrogate marker of clinical protection for mRNA-based influenza vaccines, consistent with conventional inactivated influenza vaccines.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Chong Ma, Associate Director, Moderna Therapeutics Inc.
Chong Ma, PhD, is an Associate Director at Moderna, specializing in statistical methodology and biomarker research for respiratory and latent virus vaccines and oncology therapeutics. His work focuses on developing and applying advanced statistical models to evaluate clinical biomarkers as surrogate endpoints and correlates of risk and/or protection across multiple vaccine platforms, including influenza, COVID-19, and RSV. Dr. Ma has authored several peer-reviewed publications on statistical methodology and correlates of protection modeling.
Scientific Meetings
PSI Vaccines SIG Webinar: Statistical Immune Correlate Analysis of Hemagglutination Inhibition Titers for an mRNA-based Influenza Vaccine
Date: Thursday 22nd October 2026 Time: 15:00 - 16:00 GMT Location: Online via Zoom
Who is this event intended for?Statisticians with an interest in vaccine development
What is the benefit of attending? To learn about the recent application of statistical immune correlate analysis in vaccine development. Specifically, an application of such analyses to evaluate hemagglutination inhibition titers for an influenza vaccine
Overview
Hemagglutination inhibition antibody (HAI) titers are widely utilized as correlates of protection (CoP) and surrogate endpoints for predicting influenza vaccine efficacy (VE). In the phase 3 FLUENT trial (NCT06602024), which enrolled over 40,000 participants ≥50 years, the mRNA-based seasonal influenza vaccine, mRNA-1010, demonstrated superior VE and elicited stronger antibody responses than a licensed standard-dose inactivated influenza vaccine.
Here, in the immune correlate analysis of the FLUENT trial, we evaluated hemagglutination inhibition (HAI) titers against influenza A/H1N1, A/H3N2, and B/Victoria strains as correlates of risk (CoR) and CoP for strain-specific influenza-like illness (ILI) following vaccination. Across multiple statistical and causal inference frameworks, higher Day 29 influenza A strain-specific HAI titers were consistently associated with lower ILI and higher relative VE. The estimated hazard ratios per one standard deviation increase in HAI titers were 0.48 (95% CI: 0.43–0.54; P<0.001) for A/H1N1 and 0.66 (0.58–0.74; P<0.001) for A/H3N2.
Although B/Victoria results in FLUENT were inconclusive, likely reflecting limited cases and regional variability, pooled analyses across phase 3 trials showed consistent inverse associations for both vaccines. These findings support post-vaccination HAI titers as a statistical CoP and surrogate marker of clinical protection for mRNA-based influenza vaccines, consistent with conventional inactivated influenza vaccines.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Chong Ma, Associate Director, Moderna Therapeutics Inc.
Chong Ma, PhD, is an Associate Director at Moderna, specializing in statistical methodology and biomarker research for respiratory and latent virus vaccines and oncology therapeutics. His work focuses on developing and applying advanced statistical models to evaluate clinical biomarkers as surrogate endpoints and correlates of risk and/or protection across multiple vaccine platforms, including influenza, COVID-19, and RSV. Dr. Ma has authored several peer-reviewed publications on statistical methodology and correlates of protection modeling.
Training Courses
PSI Vaccines SIG Webinar: Statistical Immune Correlate Analysis of Hemagglutination Inhibition Titers for an mRNA-based Influenza Vaccine
Date: Thursday 22nd October 2026 Time: 15:00 - 16:00 GMT Location: Online via Zoom
Who is this event intended for?Statisticians with an interest in vaccine development
What is the benefit of attending? To learn about the recent application of statistical immune correlate analysis in vaccine development. Specifically, an application of such analyses to evaluate hemagglutination inhibition titers for an influenza vaccine
Overview
Hemagglutination inhibition antibody (HAI) titers are widely utilized as correlates of protection (CoP) and surrogate endpoints for predicting influenza vaccine efficacy (VE). In the phase 3 FLUENT trial (NCT06602024), which enrolled over 40,000 participants ≥50 years, the mRNA-based seasonal influenza vaccine, mRNA-1010, demonstrated superior VE and elicited stronger antibody responses than a licensed standard-dose inactivated influenza vaccine.
Here, in the immune correlate analysis of the FLUENT trial, we evaluated hemagglutination inhibition (HAI) titers against influenza A/H1N1, A/H3N2, and B/Victoria strains as correlates of risk (CoR) and CoP for strain-specific influenza-like illness (ILI) following vaccination. Across multiple statistical and causal inference frameworks, higher Day 29 influenza A strain-specific HAI titers were consistently associated with lower ILI and higher relative VE. The estimated hazard ratios per one standard deviation increase in HAI titers were 0.48 (95% CI: 0.43–0.54; P<0.001) for A/H1N1 and 0.66 (0.58–0.74; P<0.001) for A/H3N2.
Although B/Victoria results in FLUENT were inconclusive, likely reflecting limited cases and regional variability, pooled analyses across phase 3 trials showed consistent inverse associations for both vaccines. These findings support post-vaccination HAI titers as a statistical CoP and surrogate marker of clinical protection for mRNA-based influenza vaccines, consistent with conventional inactivated influenza vaccines.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Chong Ma, Associate Director, Moderna Therapeutics Inc.
Chong Ma, PhD, is an Associate Director at Moderna, specializing in statistical methodology and biomarker research for respiratory and latent virus vaccines and oncology therapeutics. His work focuses on developing and applying advanced statistical models to evaluate clinical biomarkers as surrogate endpoints and correlates of risk and/or protection across multiple vaccine platforms, including influenza, COVID-19, and RSV. Dr. Ma has authored several peer-reviewed publications on statistical methodology and correlates of protection modeling.
Journal Club
PSI Vaccines SIG Webinar: Statistical Immune Correlate Analysis of Hemagglutination Inhibition Titers for an mRNA-based Influenza Vaccine
Date: Thursday 22nd October 2026 Time: 15:00 - 16:00 GMT Location: Online via Zoom
Who is this event intended for?Statisticians with an interest in vaccine development
What is the benefit of attending? To learn about the recent application of statistical immune correlate analysis in vaccine development. Specifically, an application of such analyses to evaluate hemagglutination inhibition titers for an influenza vaccine
Overview
Hemagglutination inhibition antibody (HAI) titers are widely utilized as correlates of protection (CoP) and surrogate endpoints for predicting influenza vaccine efficacy (VE). In the phase 3 FLUENT trial (NCT06602024), which enrolled over 40,000 participants ≥50 years, the mRNA-based seasonal influenza vaccine, mRNA-1010, demonstrated superior VE and elicited stronger antibody responses than a licensed standard-dose inactivated influenza vaccine.
Here, in the immune correlate analysis of the FLUENT trial, we evaluated hemagglutination inhibition (HAI) titers against influenza A/H1N1, A/H3N2, and B/Victoria strains as correlates of risk (CoR) and CoP for strain-specific influenza-like illness (ILI) following vaccination. Across multiple statistical and causal inference frameworks, higher Day 29 influenza A strain-specific HAI titers were consistently associated with lower ILI and higher relative VE. The estimated hazard ratios per one standard deviation increase in HAI titers were 0.48 (95% CI: 0.43–0.54; P<0.001) for A/H1N1 and 0.66 (0.58–0.74; P<0.001) for A/H3N2.
Although B/Victoria results in FLUENT were inconclusive, likely reflecting limited cases and regional variability, pooled analyses across phase 3 trials showed consistent inverse associations for both vaccines. These findings support post-vaccination HAI titers as a statistical CoP and surrogate marker of clinical protection for mRNA-based influenza vaccines, consistent with conventional inactivated influenza vaccines.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Chong Ma, Associate Director, Moderna Therapeutics Inc.
Chong Ma, PhD, is an Associate Director at Moderna, specializing in statistical methodology and biomarker research for respiratory and latent virus vaccines and oncology therapeutics. His work focuses on developing and applying advanced statistical models to evaluate clinical biomarkers as surrogate endpoints and correlates of risk and/or protection across multiple vaccine platforms, including influenza, COVID-19, and RSV. Dr. Ma has authored several peer-reviewed publications on statistical methodology and correlates of protection modeling.
Webinars
PSI Vaccines SIG Webinar: Statistical Immune Correlate Analysis of Hemagglutination Inhibition Titers for an mRNA-based Influenza Vaccine
Date: Thursday 22nd October 2026 Time: 15:00 - 16:00 GMT Location: Online via Zoom
Who is this event intended for?Statisticians with an interest in vaccine development
What is the benefit of attending? To learn about the recent application of statistical immune correlate analysis in vaccine development. Specifically, an application of such analyses to evaluate hemagglutination inhibition titers for an influenza vaccine
Overview
Hemagglutination inhibition antibody (HAI) titers are widely utilized as correlates of protection (CoP) and surrogate endpoints for predicting influenza vaccine efficacy (VE). In the phase 3 FLUENT trial (NCT06602024), which enrolled over 40,000 participants ≥50 years, the mRNA-based seasonal influenza vaccine, mRNA-1010, demonstrated superior VE and elicited stronger antibody responses than a licensed standard-dose inactivated influenza vaccine.
Here, in the immune correlate analysis of the FLUENT trial, we evaluated hemagglutination inhibition (HAI) titers against influenza A/H1N1, A/H3N2, and B/Victoria strains as correlates of risk (CoR) and CoP for strain-specific influenza-like illness (ILI) following vaccination. Across multiple statistical and causal inference frameworks, higher Day 29 influenza A strain-specific HAI titers were consistently associated with lower ILI and higher relative VE. The estimated hazard ratios per one standard deviation increase in HAI titers were 0.48 (95% CI: 0.43–0.54; P<0.001) for A/H1N1 and 0.66 (0.58–0.74; P<0.001) for A/H3N2.
Although B/Victoria results in FLUENT were inconclusive, likely reflecting limited cases and regional variability, pooled analyses across phase 3 trials showed consistent inverse associations for both vaccines. These findings support post-vaccination HAI titers as a statistical CoP and surrogate marker of clinical protection for mRNA-based influenza vaccines, consistent with conventional inactivated influenza vaccines.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Chong Ma, Associate Director, Moderna Therapeutics Inc.
Chong Ma, PhD, is an Associate Director at Moderna, specializing in statistical methodology and biomarker research for respiratory and latent virus vaccines and oncology therapeutics. His work focuses on developing and applying advanced statistical models to evaluate clinical biomarkers as surrogate endpoints and correlates of risk and/or protection across multiple vaccine platforms, including influenza, COVID-19, and RSV. Dr. Ma has authored several peer-reviewed publications on statistical methodology and correlates of protection modeling.
Careers Meetings
PSI Vaccines SIG Webinar: Statistical Immune Correlate Analysis of Hemagglutination Inhibition Titers for an mRNA-based Influenza Vaccine
Date: Thursday 22nd October 2026 Time: 15:00 - 16:00 GMT Location: Online via Zoom
Who is this event intended for?Statisticians with an interest in vaccine development
What is the benefit of attending? To learn about the recent application of statistical immune correlate analysis in vaccine development. Specifically, an application of such analyses to evaluate hemagglutination inhibition titers for an influenza vaccine
Overview
Hemagglutination inhibition antibody (HAI) titers are widely utilized as correlates of protection (CoP) and surrogate endpoints for predicting influenza vaccine efficacy (VE). In the phase 3 FLUENT trial (NCT06602024), which enrolled over 40,000 participants ≥50 years, the mRNA-based seasonal influenza vaccine, mRNA-1010, demonstrated superior VE and elicited stronger antibody responses than a licensed standard-dose inactivated influenza vaccine.
Here, in the immune correlate analysis of the FLUENT trial, we evaluated hemagglutination inhibition (HAI) titers against influenza A/H1N1, A/H3N2, and B/Victoria strains as correlates of risk (CoR) and CoP for strain-specific influenza-like illness (ILI) following vaccination. Across multiple statistical and causal inference frameworks, higher Day 29 influenza A strain-specific HAI titers were consistently associated with lower ILI and higher relative VE. The estimated hazard ratios per one standard deviation increase in HAI titers were 0.48 (95% CI: 0.43–0.54; P<0.001) for A/H1N1 and 0.66 (0.58–0.74; P<0.001) for A/H3N2.
Although B/Victoria results in FLUENT were inconclusive, likely reflecting limited cases and regional variability, pooled analyses across phase 3 trials showed consistent inverse associations for both vaccines. These findings support post-vaccination HAI titers as a statistical CoP and surrogate marker of clinical protection for mRNA-based influenza vaccines, consistent with conventional inactivated influenza vaccines.
Registration
This webinar is free to attend for PSI Members & Non-Members. To register for this event, please click here.
Speaker details
Speaker
Biography
Chong Ma, Associate Director, Moderna Therapeutics Inc.
Chong Ma, PhD, is an Associate Director at Moderna, specializing in statistical methodology and biomarker research for respiratory and latent virus vaccines and oncology therapeutics. His work focuses on developing and applying advanced statistical models to evaluate clinical biomarkers as surrogate endpoints and correlates of risk and/or protection across multiple vaccine platforms, including influenza, COVID-19, and RSV. Dr. Ma has authored several peer-reviewed publications on statistical methodology and correlates of protection modeling.
Upcoming Events
PSI Book Club: Change: How organisations achieve hard-to-imagine results in uncertain and volatile times
Organizations have to adapt to the transforming landscape of our industry to ensure they continue to be successful in the future. Many of us are feeling the impact of organizational change. By reading John P Kotter’s book we can understand about organizational change and learn how to thrive, rather than just survive, through change.
Change, by John P Kotter (and his team), is a summary of all that he has learned over his decades of research and leading change. His book describes why many current approaches to change are inadequate and explains why new solutions need to give people a voice and a role in a new, change-embracing organization.
Develop your understanding of organisational change and become empowered to be part of your organisation’s change, by reading Change by John P Kotter and joining the Sept-Dec 2025 book club. You will be invited to join facilitated discussions of the concepts and ideas and apply knowledge from the book in-between sessions.
Joint PSI/EFSPI, PHUSE, ASA Safety Working Group Webinar Series: Scientific Evaluation of Safety Data: A Learning and Decision-Making Approach
The webinar will explore how different clinical safety questions can be translated into appropriate estimands and aligned with corresponding estimators.
Joint PSI/EFSPI Visualisation SIG 'Wonderful Wednesday' Webinars
Our monthly webinar explores examples of innovative data visualisations relevant to our day to day work. Each month a new dataset is provided from a clinical trial or other relevant example, and participants are invited to submit a graphic that communicates interesting and relevant characteristics of the data.
Date: 18 November 2026
This is an excellent opportunity for students to find out more about the field of medical statistics, talk to people from different organisations and make contacts for the future. All students currently studying for a mathematics or statistics-related BSc, MSc or PhD are invited to attend, and we welcome interest from exhibitors too.
Our monthly webinar series allows attendees to gain practical knowledge and skills in open-source coding and tools, with a focus on applications in the pharmaceutical industry.
Aligning Estimation with the Clinical Question of Interest
This webinar will focus on aligning estimation to estimands. How do different strategies for handling intercurrent events and missing data handling influence the choice of estimation method, with illustration using a case study.
This networking event is aimed at statisticians that are new to the pharmaceutical industry who wish to meet colleagues from different companies and backgrounds.
PSI Careers Coaching Series: Peer Support Initiative
This 10-month peer support programme is aimed at professionals with five or more years of experience who are seeking structured development and connection with peers at a similar career stage. Through 5 bi-monthly topics, participants will engage in coach-led presentations, small-group discussions, and regular progress reviews focused on achieving tangible outcomes.
Viatris is a global healthcare company uniquely positioned to bridge the traditional divide between generics and brands, combining the best of both to more holistically address healthcare needs globally.
Viatris is a global healthcare company uniquely positioned to bridge the traditional divide between generics and brands, combining the best of both to more holistically address healthcare needs globally.
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